pancancer_analysis

Scripts used to analyse the PCAWG datasets

1. Motif detection and annotation

GenerateMotifsFIMO.py based on datafiles/Motifs/

2. Download datasets

• ENCODE_searchTerms_29Nov.txt: shows steps for generating metadata for downlaoding

• ParseCellInfo.py: Downloads and processes datasets based on datafiles/CellInfoDict

• GetDataSetsAPI.py: dowanlods RNA-seq from ENCODE and reports expression level per gene per sample

3. Generate database tables and retrieve data

• score_motifs_tissuepertable.py: extract motifs per TF and annotates them based on data obtained from (1) and (2). Reads parameters from score_motifs_param_regulatorymotifs.conf

• GetDBData_TrainingSets.py: get motifs from MPRAs and inactive genes

• WeightFeatures.py: Get weights per feature for motif scoring based on active and inactive motifs

• RetrieveDB.py: get motif info from the motif datbase

4. Mutation annotation

5. Element annotation

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6. Downstream analysis